Spectrum sensing is needed in cognitive radios to find empty slots in the radio spectrum which can subsequently be used in an opportunistic manner. The cognitive radio must be able to detect a primary user at a low power level and avoid causing interference to it. Generally it is assumed to use the actual mobile terminals operating within the network as the cognitive radios that also sense the spectrum quality. The spectrum sensing task can be enhanced by utilizing collaboration among users. Having many users analyze the same part of the spectrum simultaneously can result in an enhanced detection probability of low level signals when the results are merged. Similarly, having each individual user sense a smaller part of the spectrum at a given time instance would allow for using simpler and more power efficient spectrum sensing techniques, since each individual user need only sense a portion of the entire spectrum but if the information is properly managed each user benefits from the other users' spectrum measurements also. By using collaboration among the users, one can also avoid the so-called hidden node problem where the primary user cannot be detected by using a single terminal due to channel propagation effects such as shadowing or fading. The effects of propagation can be mitigated when multiple terminals in different locations are used for the spectrum sensing.
So the spectrum sensing task can in theory be shared among the various users in order to obtain savings in power consumption at the individual mobile users, to reduce the amount of data to be transmitted by those individual users, and consequently to facilitate the use of simpler sensing techniques in each individual user as compared to having individual terminals measure the entire spectrum in use across the network. One practical problem with collaboration is that the selection, control, and resultant handling of the collaborative nodes represent a control signaling overhead that occupies additional bandwidth because the collaborative nodes need to be controlled independently. Thus the potential spectrum savings by allocating bandwidth more efficiently in view of the spectrum sensing by the mobile terminals is offset, often more than offset, by the coordination required to get those mobile terminals to sense portions of the spectrum. This is particularly true when one tries to incorporate diversity into spectrum sensing so as to avoid the hidden node problem above.
There are not that many prior art systems known to the inventors. A first prior art approach to be considered is sensor networks where the communication of sensors is operating based on the random communications. In this first approach the sensor networks are not collaborating in the spectrum sensing phase. A second prior art approach that might be relevant is frequency hopping systems where the frequencies are utilized based on the beforehand agreed scheme. To avoid interference the frequency hopping systems generally impose some pseudo-randomness into the hopping pattern used by the individual mobile terminals. These frequency hopping schemes are used to determine the time and frequency slots for traffic though, and to the knowledge of the inventors are not employed for spectrum sensing purposes. Frequency hopping communication systems generally seek to avoid many users on the same band simultaneously so as to avoid collisions, whereas for sensing this is an advantage in that there is diversity gains and performance improvement by having multiple users sensing the same band simultaneously. Generally, a sensing system would be designed to result in collisions in a controlled manner, and so spectrum sensing systems are inherently different from frequency-hop based communication systems.
What is needed in the art is a way to sense a radio spectrum that is low in signaling overhead yet still measures the same spectrum from different locations at the same time so as to give the advantages of diversity. The practical constraints of any reasonable approach are that individual mobile terminals that may measure that spectrum quality have a limited power supply, and that spectrum sensing should not interfere with user data being transmitted in that same network for which the spectrum is being sensing and the measurement reports sent for compilation and more efficient deployment of that same radio spectrum.